An Integrated Traffic and Pedestrian Vision System

This page describes the Integrated Traffic and Pedestrian Vision System
developed by a collaboration between the vision groups at Leeds
and Reading Universities
as part of the EPSRC's IMV program (EPSRC Grant GR/K46620).

The project combines two model-based tracking systems:

Using active shape models to track non-rigid objects, in this case people.
(Leeds)

Using geometric 3D models to track rigid objects: in this case cars. (Reading)

Mutual occlusion between vehicles and people is handled by passing 2D 'occlusion
masks' between the two systems.

Two complementary approaches for analysing the interactions between
people and vehicles were explored:

At Leeds we have shown how to detect atypical events using features of
the spatio-temporal trajectories of people in relation to vehicles. To
do this, the trajectories of people are compared with a probabilistic model
for the distribution of these features obtained by observing large numbers
of typical interactions.

At Reading they have developed a system to produce natural language descriptions
of object interactions using Bayesian belief nets.

Heres what Don Braggins had to say about this project in the Oct 97 issue
of Image Processing Europe:

Last Year I reviewed Daniel Crevier's book 'AI - the tumultuous
history of the search for artificial intelligence' in which he relates
how in 1966 Marvin Minsky set a first year undergraduate, Gerald Sussman,
the task of connecting a television camera to a computer and getting the
machine to describe what it saw. He did not succeed, but a joint project
between Prof. David Hogg's group at Leeds University and Dr Tieniu Tan's
at Reading (taking over the reins from the late Geoff Sullivan) comes close
to achieving that goal. They have been able to automatically annotate image
sequences to say, for instance, that 'Pedestrian n is now walking
slowly in front of parked vehicle m' where n and m
are simply the sequential numbers relating to appearance in the scene.
Based on work David Hogg's group has done in finding algorithms to identify
suspicious behaviour in car parks, it should not be long before the annotation
can be extended to say 'Pedestrian n looks about to nick something
out of vehicle m better have a human look at the image on the monitor'.

The work also featured on BBC Look North (30/3/98), Radio 5 Live (30/3/98),
The
Daily Telegraph (2/4/98), OCE magazine. According to BBC breakfast
(23/4/98) we're a 'civil liberties nightmare.'

Fitting models to cars and people

The Likelihood of a particular trajectory

MPEG movie (2MB) assessing the likelihood of
a particular trajectories. Dots above the heads indicate likelihood of
a particular trajectory. For this example the positions of cars were estimated
by hand.

There are several other pages mainly meant for internal consumption,
but you may find these of interest.